Elemental Machines adds LabOps scheduling

Hospital, pharmaceutical and medical enterprises face many of the same problems managing their lab equipment as enterprises before the rise of virtual machines and cloud services. In enterprise infrastructure, the popularity and capabilities of better cloud management tools eventually gave rise to devops for bridging the gap between application development and operational deployment. 

A new generation of LabOps tools is starting to bridge a similar gap between experimental design and laboratory operations. Elemental Machines, a pioneer in LabOps, has added new lab equipment scheduling capabilities to its LabOps tools. This provides a functional view of all available equipment in a specific area to enable easier coordination between teams in different locations. 

The rise of LabOps

Elemental Machines is the third startup founded by Sridhar Iyengar in 2014. His first company, AgaMatrix, makes store brand glucose meters for CVS, Target pharmacy, Kroger and Amazon. His second, Misfit Wearables, makes fitness trackers. Iyengar told VentureBeat that Elemental Machines “takes everything I learned at my second startup and applied it to all the headaches and problems I had at my first startup.” 

One of his biggest challenges was on the manufacturing side, where they had to understand what was happening in a factory in another country. This insight gave form to the idea of LabOps to simplify data exchange for lab equipment. 

LabOps as a field builds on previous work to bring order to health research. Existing tools in this field include laboratory information management systems (LIMS) for managing samples and associated data and electronic lab notebooks (ELN) for documenting medical research. 

LabOps extends data management control to the lab equipment itself. Not only is scientific data made available and embedded into LIMS/ELN systems, but it also captures historical data that can be used to optimize equipment settings. This allows scientists and lab staff to focus on their projects instead of trying to figure out how to translate an experimental design into the settings required for each piece of equipment. 

This helps create a laboratory digital twin to provide real-time alerting and monitoring of any piece of equipment and the environmental conditions in the lab. This can help consolidate alerting and monitoring, improve asset and data management, streamline quality assurance and quality control and analyze usage. 

Better scheduling

The new scheduling capabilities make it easier for teams to coordinate experiments from different groups within a research organization. This is important because many experiments require coordinating multiple steps that need to be conducted in the appropriate sequence and conditions. 

Local managers can invite an unlimited number of coworkers to collaborate around specific equipment and track each reservation to a particular protocol, including all the equipment details needed to repeat tests anywhere. Managers can also assign primary investigators to each reservation, making it easier to report results. 

Many scientists and lab professionals use “defensive booking,” where they book equipment for two to three times longer than they actually need, said Samantha Black, head of content at Elemental Machines. Other labs do not use any scheduling procedures and two team members may show up expecting to use the same equipment at the same time. Elemental Calendar was designed to prevent these issues, as well as providing insight into actual equipment usage and helping inform maintenance schedules and purchasing decisions. 

Valuate research predicts the global lab automation market could grow from $13.7 billion in 2022 to $19.8 billion in 2028. LabOps plays an essential role in driving efficiency in the research process for the pharmaceutical market, which Statista pegged at $1.27 trillion in 2020. LabOps competitors include Roche Viewics, Lab Fellows and Artificial. This kind of technology could also help enterprises create their own experiments-as-code platform. 

Labs still have a ways to go to get to the kinds of dynamic scalability available with cloud services, but this is an essential step in helping medical research organizations optimize their lab spend.